"empirical risk minimization" Papers

16 papers found

Boosting Test Performance with Importance Sampling--a Subpopulation Perspective

Hongyu Shen, Zhizhen Zhao

AAAI 2025paperarXiv:2412.13003

Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Power

Lijia Yu, Yibo Miao, Yifan Zhu et al.

ICLR 2025
1
citations

High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws

Muhammed Ildiz, Halil Gozeten, Ege Taga et al.

ICLR 2025arXiv:2410.18837
13
citations

On Agnostic PAC Learning in the Small Error Regime

Julian Asilis, Mikael Møller Høgsgaard, Grigoris Velegkas

NEURIPS 2025spotlightarXiv:2502.09496

Prediction-Powered Causal Inferences

Riccardo Cadei, Ilker Demirel, Piersilvio De Bartolomeis et al.

NEURIPS 2025arXiv:2502.06343
6
citations

Purifying Approximate Differential Privacy with Randomized Post-processing

Yingyu Lin, Erchi Wang, Yian Ma et al.

NEURIPS 2025spotlightarXiv:2503.21071
2
citations

SEBRA : Debiasing through Self-Guided Bias Ranking

Adarsh Kappiyath, Abhra Chaudhuri, AJAY JAISWAL et al.

ICLR 2025arXiv:2501.18277
2
citations

Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning

Idan Attias, Steve Hanneke, Arvind Ramaswami

NEURIPS 2025spotlightarXiv:2506.00135

Adversarially Robust Hypothesis Transfer Learning

Yunjuan Wang, Raman Arora

ICML 2024

Collaborative Learning with Different Labeling Functions

yuyang deng, Mingda Qiao

ICML 2024arXiv:2402.10445
1
citations

From Inverse Optimization to Feasibility to ERM

Saurabh Mishra, Anant Raj, Sharan Vaswani

ICML 2024arXiv:2402.17890
4
citations

How to Escape Sharp Minima with Random Perturbations

Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra

ICML 2024arXiv:2305.15659
14
citations

Multi-Dimensional Fair Federated Learning

Cong Su, Guoxian Yu, Jun Wang et al.

AAAI 2024paperarXiv:2312.05551
11
citations

On the Asymptotic Distribution of the Minimum Empirical Risk

Jacob Westerhout, TrungTin Nguyen, Xin Guo et al.

ICML 2024

Optimal Differentially Private Model Training with Public Data

Andrew Lowy, Zeman Li, Tianjian Huang et al.

ICML 2024arXiv:2306.15056
7
citations

Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective

Yulong Zhang, Yuan Yao, Shuhao Chen et al.

ICML 2024